Artificial intelligence

“Our computers were appallingly stupid”

Mario Sela, mobility expert at Bitkom, Germany's digital association, on the technological and social dimensions of artificial intelligence, the potential for optimization that AI offers for mobility, and the question of who should have the final say in automated traffic systems: the machine or the human?

Mr. Sela, Tesla founder Elon Musk sees artificial intelligence as "the greatest risk to our civilization". Physicist Stephen Hawking warns that artificial intelligence could replace humans. Do you think that the concerns of these two well-known sceptics are understandable??

Such concerns are discussed in public repeatedly, and are shared by some distinguished thought-leaders in the technology scene. However, what is being ignored here is the fact that the vast majority of experts see things differently. The risk that the automatic parking system in your car or an intelligent training assistant at work will achieve world domination is very small. We are seeing better and better AI systems, each of which has been trained for a particular task and in some cases can do it better than we humans can. But a machine that is particularly good at diagnosing illnesses can only do just that. It will not be booking trips for me or cleaning my apartment.

How do you rate such warnings that tend to elicit a strong echo in the media? Are they simply cases of counterproductive panic-mongering that hampers development – or reasonable appeals to politicians to think about introducing regulations as soon as possible?

We need to educate people in a better and more broad-based way so that they understand what artificial intelligence can and cannot do. Artificial intelligence is a key technology that will profoundly change our economic, political and social structures in the future. What we urgently need is a strategy at the federal level for the development and use of artificial intelligence. In the area of AI research, Germany is in an excellent position. But if we spend the next few years simply debating the pros and cons of the technology, we will lose out internationally. Both China and Russia are setting an example by placing AI at the top of their agendas and providing adequate financial resources.

In your view, what kind of regulations would be needed?

In addition to having an AI strategy and promoting the subject itself, it is also critical that we look into the risks it may generate. A strategic process to assess the potentials and risks involved in AI should be set up. At the European level, Germany should also campaign for the further development of data privacy and protection in connection with AI. Here a “regulated co-regulation” may be the approach of choice when it comes to implementing data protection rules for AI applications. Under this approach, companies would use best practices to develop codes of conduct that the EU Commission or the supervisory authorities would then recognize as compliant with the applicable laws. AI is of fundamental importance to the development of our future digital society. That is why we need a set of cornerstones for digital ethics. These should be developed in partnership between society, business and politics.

In which areas of intelligence are machines already superior to humans – and in which ones do they still have some catching-up to do?

The idea of intelligent machines whose performance is equal or even superior to that of humans has been inspiring our imagination for a long time. Whether clever on-board computers, human-like androids or the merciless Terminator, science-fiction literature and the movie industry have explored the theme of artificial intelligence again and again. By comparison, the computers on our desks used to be terribly stupid for the longest time. In recent years, all this has changed. Intelligent private assistants on smartphones or in our living rooms who can engage in a real dialog with us, automatic translators that do not simply produce gibberish, or cars that drive from A to B all by themselves without causing an accident – all these are examples for AI systems that have made something approaching a breakthrough into our everyday reality.

What is new about AI, compared to classical electronic data processing systems, is the learning component. It's no coincidence that terms like ‘machine learning’ or ‘deep learning’ are closely related to AI, as learning is central. There is a huge benefit in this. It's almost impossible to describe to a software program what a chair really is and the many shapes and designs it can take. A learning system that has been trained with a few hundred photos of chairs is then able to decide quite well as to whether a specific object is a chair or not. Or think of autonomous driving. Explicitly explaining to a conventional system how to respond in any thinkable traffic situation is almost impossible. In contrast, a learning system can master this task.

And how will that all look in 20 years’ time?

In just a few years’ time, many products and services will be equipped with machine intelligence or even have been fundamentally shaped by it. Self-driving cars, resource-efficient logistics processes or effective police work – AI will support people in all kinds of areas and relieve them of routine tasks. It's not about an AI system replacing a human doctor. Rather, it's about intelligent systems that work for the human doctor.

Bitkom survey: "Eight out of ten German citizens are sure that AI can improve traffic control and thus reduce traffic jams."

You recently surveyed people in Germany for their opinion on artificial intelligence. What was the result?

We found that Germans are divided on the fundamental question of whether AI is more of an opportunity or rather a risk. There is a difference here between German citizens in general and those who know more about AI. In the better informed group, 57 percent say that artificial intelligence offers opportunities, with only 38 percent believing that the dangers outweigh the benefits. Above all, our study also revealed that if the question does not refer to the term artificial intelligence, but rather to actual applications, people tend to be very open to this technology.

Does this mean that Germans are more open-minded or less open-minded in this respect than people in other parts of the world?

Germans are very open to AI – especially if you do not ask about the general term, but about real applications. But despite this fundamental openness to AI and its opportunities, there are also fears and worries. For example, respondents feared that the use of AI will open the door to the abuse of power and to manipulation, and that decisions will be advertised as fact-based while they actually reflect the programmer's prejudices that are now built into the systems. One in two respondents even believes that AI will rob people of their competence to decide for themselves – and that AI will turn against humans.

In which areas of life do respondents expect the most support from AI?

If you ask German citizens, a clear majority are of the opinion that AI is able to resolve some of the great challenges for our society. Eight out of ten German citizens are sure that AI can improve traffic control and thus reduce traffic jams. Just as many believe that AI will allow industry to transfer physically demanding activities to machines. Just over two thirds are confident that AI applications will accelerate administrative work, boost innovation in research and help customer service staff provide more reliable support. Likewise, a majority assume that the use of AI will enable police to investigate and solve crimes more quickly, and that diagnoses in health care will improve with the assistance of AI.

Do these results more or less fit in with your expectations?

The results were more positive than we had expected.

Handover of the key: “Machines can make certain decisions much faster and thus contribute to greater safety in the transport system.”

In your opinion, where is the greatest potential for the optimization of mobility using AI applications?

It is precisely in the field of mobility that we are already envisaging a variety of possibilities for the application of AI today. This starts with route planning and goes a long way beyond the self-driving car.

On a timeline, where would you put these technological advances in traffic engineering? By when do you expect to see developments based on AI?

Accurate forecasting is very difficult in the digital world. You just have to remember that the first iPhone arrived on the market only a little over ten years ago, and bring to mind all the changes that the existence of smartphones has initiated. What is more, development in the area of traffic is not just about technological breakthroughs, but always also about adapting the legal framework accordingly. At last year’s IAA – the International Motor Show in Germany – we asked a number of managers from the automotive industry, and the majority of them arrived at this assessment: In 50 years’ time, only self-driving cars will be registered in Germany.

In 50 years’ time, only self-driving cars will be registered in Germany.

Mario Sela, Mobility expert at the German digital association Bitkom

Can the continuous improvements in IT security systems keep up with this pace of change?

This is not a question of "can", but a question of "must". IT security and privacy are key issues. It is precisely in this area that German companies and researchers have an excellent reputation and a great deal of expertise.

In your opinion, who should have the last word in the automated traffic systems of the future – the machine or the human being?

Automated systems must be designed in such a way that they are geared to the well-being of man. So, if a decision made by a machine makes a greater contribution to safety, comfort or efficiency in the transport system, then the machine should make that choice, for example in critical situations when very fast reactions and responses are required.

How would the division of tasks between man and machine look in practice?

Machines can make certain decisions much faster and thus contribute to greater safety in the transport system – let's just think of the reaction time of about 1 second that human beings need before they initiate emergency braking, which at 50 kilometers per hour extends a car’s stopping distance by about 14 meters. Here a machine can decide much faster and stop the car more efficiently. With regard to the overall system, however, humans should always have the possibility of overriding the mechanical system – for example, with an emergency brake function in a driverless shuttle that allows the vehicle to stop safely at the roadside.

Mario Sela’s field of research at Bitkom is the digital transformation of the mobility market, with special focus on a whole range of concepts, from innovative sharing services and smart transportation of people and goods by road and rail right up to autonomous vehicles.

During the 15 years he has worked in the business, he has developed communication and products offers for political stakeholders and for the mobility sector. His main focus lies on taking an overall systemic view of mobility and on activating the market for the corresponding offers. Before joining Bitkom in 2016, Mario Sela worked for Deutsche Bahn AG, Volkswagen, Toll Collect and Daimler AG, among others.